Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials

Comparison of machine learning clustering algorithms for detecting heterogeneity of treatment effect in acute respiratory distress syndrome: A secondary analysis of three randomised controlled trials

Background: Heterogeneity in Acute Respiratory Distress Syndrome (ARDS), as a consequence of its non-specific definition, has led to a multitude of negative randomised controlled trials (RCTs). Investigators have sought to identify heterogeneity of treatment effect (HTE) in RCTs using clustering alg...

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Bibliographic Details
Main Authors: Pratik Sinha, Alexandra Spicer, Kevin L Delucchi, Daniel F McAuley, Carolyn S Calfee, Matthew M Churpek
Format: article
Language:EN
Published: Elsevier 2021
Subjects:
ARDS
RCTs
Clustering
machine learning
LCA
Heterogeneity of treatment effect
Medicine
R
Medicine (General)
R5-920
Online Access:https://doaj.org/article/dcd0c2641c8d430e8bbc69ed3dea44b9
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